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Generalized economic model, risk analysis framework and decision support system for the analysis and evaluation of capital investment projects

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Title: Generalized economic model, risk analysis framework and decision support system for the analysis and evaluation of capital investment projects
Author: Abdel-Aziz, Ahmed Mohamed
Degree: Doctor of Philosophy - PhD
Program: Civil Engineering
Copyright Date: 2000
Issue Date: 2009-07-27
Series/Report no. UBC Retrospective Theses Digitization Project [http://www.library.ubc.ca/archives/retro_theses/]
Abstract: The goal of this thesis is to contribute to the knowledge base for making high quality decisions about capital investment projects. To achieve this goal, a generalized economic model, risk analysis framework, and decision support system for the evaluation and risk analysis of capital investment projects are developed. A detailed investigation of the characteristics of capital investment projects for which the economic model, risk analysis framework and decision support system are to be built is made. A framework called "requirement structure" is introduced in order to investigate the characteristics of a project during its life cycle. A number of infrastructure transportation projects developed under alternative procurement modes in the U.S., U.K., and Canada are used in this study. Capital investment projects are a feature of several industries, markets and business sectors. These markets and business sectors have different characteristics and require the use of a variety of methods in preparing estimates and forecasts. An objective of the thesis deals with modeling such diversity. To achieve this objective, a generalized economic model is developed with a multipurpose hierarchical network-based time function structure. One concept behind the generalized model is that of cash flow classification. A classification represents a domain, e.g. maintenance or finance, and possesses the properties and methods of that domain. This allows a cash flow of a classification type to inherit its domain's properties and methods. Another concept behind the generalized model is shape functions, which allows the variables of the generalized model to change over time according to a selected pattern. More importantly, shape functions serve in converting an estimate into an expenditure flow. The model structure is organized in four components reflecting four classification domains in capital investment projects namely, capital expenditure, revenue, operation and maintenance, and project financing. The basic elements in a component are called constructs. Each construct represents a cash flow that has the same classification type of the component and consequently inherits its properties and methods. With the generalized economic model, a project economic structure can be formulated with any required properties and methods. The generalized model embraces a broad range of periodic and cumulative cash flows and performance measures such as net present value, internal rate of return, total costs (e.g. total construction cost), life cycle cost, total revenues, debt service coverage ratio, loan life cover ratio, and benefit cost ratios. To model the uncertainties inherent in the estimates of variables and economic indicators of capital investment projects, a risk analysis framework is introduced. The framework uses an analytical two- and four-moment approach that directly derives the four moments of the performance measures in the generalized model regardless of how complicated their economic structure might be. The framework reduces the necessity of computing intermediate moments as in other moment approaches. A rigorous and expanded derivation for the four moments of a system function is introduced for the framework in order to enhance the accuracy over the standard moment approach. Considerable flexibility in terms of several types of methods, e.g. percentile values, moments, and full probability distribution is introduced for modeling the uncertainty of variables in the generalized model. This provides flexibility over the simulation risk analysis approach that works only with full probability distributions. Pearson and Schmeiser-Deutsch distribution families are used to qualify/fit a distribution model for a performance measure based to its moments. A practical implementation of the generalized model and the risk analysis framework through a decision support system, called Evaluator, is presented. The system has three components: data, model, and interface/dialogue components and makes use of existing software tools. Two examples are presented in order to validate the output of the system and to show application of the system to a transportation project. Decision makers in the public and private sector should find the system to be an effective tool to assist in making decisions regarding the procurement, investment, financing, and risk allocation of capital investment projects.
Affiliation: Applied Science, Faculty of
URI: http://hdl.handle.net/2429/11361
Scholarly Level: Graduate

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